ssingha@gitam.edu
LinkedIn
Google Scholar
Scopus
ORCiD
Dr. Sudhakar Singha, hailing from West Bengal, holds an M.Tech degree from NIT Raipur, where he graduated as a gold medalist, securing the first position in M.Tech. He later earned his Ph.D. from IIT (ISM) Dhanbad. His research interests encompass groundwater quality and quantity assessment, groundwater vulnerability analysis, human health risk analysis, and the application of AI/ML in water resource management.
Research Publications
- Pasupuleti S; Singha S.S; Singha S; Kumar S, Singh R; Dhada I. (2022). “Groundwater characterization and non-carcinogenic and carcinogenic health risk assessment of nitrate exposure in the Mahanadi River Basin of India”. Journal of Environmental Management, v. 319, p. 1-13, https://doi.org/10.1016/j.jenvman.2022. 115746, (Elsvier, SCI, Scopus, I.F: 8.91).
- Singha, S.S., Pasupuleti, S., Singha S., Venkatesh A.S. (2022). “Knowledge-driven and machine learning decision tree-based approach for assessment of geospatial variation of groundwater quality around coal mining regions, Korba district, Central India”. Environmental Earth Sciences, v. 81, p. 1-13, https://doi.org/10.1007/s12665-021-10147-1, (Springer, SCI, Scopus, I.F: 3.119).
- Singha, S., Pasupuleti, S., Singha, S.S., Singh, R. and Kumar, S., 2021. “Prediction of groundwater quality using efficient machine learning technique”. Chemosphere, v.276, p.130265, https://doi.org/10.1016/j.chemosphere.2021.130265 (Elsvier, SCI, Scopus, I.F: 8.943).
- Singha, S., Pasupuleti, S., Singha, S.S., Kumar, S. (2020). “Effectiveness of groundwater heavy metal pollution indices studies by deep-learning”. Journal of Contaminant Hydrology, p.103718. https://doi.org/10.1016/j.jconhyd.2020.103718. (Elsevier, SCI, Scopus, I.F: 4.184).
- Singha, S.S., Pasupuleti, S., Singha, S., Singh, R. and Venkatesh, A.S. (2019). “Analytic network process based approach for delineation of groundwater potential zones in Korba district, Central India using remote sensing and GIS”. Geocarto International, v.34, pp.1-23. https: //doi.org/10.1080/10106049.2019.1648566. (Taylor & Francis, SCI/SCIE, Scopus, I.F: 3.450).
Ongoing Research Projects
-
AI/ML-based Qualitative and quantitative assessment of groundwater in Raipur district, Chhattisgarh, Central India, Funded by SERB-CRG (Govt. of India)
Expertise
-
Groundwater quality and quantity assessment
-
Geospatial analysis for groundwater vulnerability
-
Groundwater transport modeling
-
Human health risk analysis
-
AI/ML application in the field of water resources
Authored Books
-
Water Resources
